The embodiments described herein relate generally to analyzing remotely-sensed data related to agriculture and, more particularly, to generating information products based on remotely-sensed data.
At least some known methods for processing multispectral (MS) imagery using a single formula that converts MS data into a single vegetation index (VI) based on typically two key spectral bands. For example, the two most often used spectral bands are red-light (RL) with wavelengths near 680 nanometers (nm) and a near-infrared, Band A (NA) with wavelengths near 830 nm. Moreover, at least some known methods require that the RL and NA raster values be converted to calibrated reflectance factor (RF) values.
Moreover, at least some known methods were defined with the expectation that input spectral “brightness” digital numbers (DNs) are valid reflectance factors known to be absolutely accurate. For example, at least some known methods use raw source-imagery DNs. Other known methods use valid, absolutely accurate reflectance factors. However, obtaining accurate values for RF, even for a limited number of spectral bands, is difficult and expensive to complete. Without accurate RF values, some known methods for processing MS imagery are invalid. Moreover, the single VI that is generated by some known methods does not relate well to one or more generally important biophysical properties of vegetation analysis, such as green biomass density (GBD), green leaf area index (GLAI), and/or absorbed photosynthetically-active radiation (APAR). Furthermore, at least some known methods that use valid, absolutely accurate reflectance factors include fixed coefficients that are not accurate across large time periods, such as a time period lasting years after an initial definition of the coefficients for an initial set of reflectance factor values.
Moreover, at least some known methods for processing MS imagery use pixel values obtained using a specific MS system, such as the Landsat 1, 2, 3, or 4's Multispectral Scanner System (MSS) or Landsat 4's Thematic Mapper (TM). Accordingly, only those spectral bands obtained by MSS or TM were available for use by such methods. Moreover, such methods included the use of fixed-value coefficients that are only useful when applied to the pixel values obtained by MSS or TM and, only under conditions where solar illumination was similar. As such, use of such methods is restricted. Furthermore, at least some known methods for processing MS imagery are susceptible to unwanted variation caused by hill shading and the like, which is known as brightness noise (BN), and are also susceptible to soil noise (SN). Some other methods are less susceptible to SN, but they use only two spectral bands or use a blue light (BL) band that is not available on all spacecraft-based imaging systems.